Reproduction Data

• To effectively troubleshoot an issue, it helps to know how it happened and what steps can be taken to reproduce the issue. Data surrounding the environment that the issue occurs in, such as operating system (OS), OS version, how many times it happens and how frequently can give the investigators of the issue a better direction to head in as they attempt to isolate the root cause of the issue.
  
  

Version Data

• Collecting information on the version, or build, of the product or software the user is reporting is also an effective way to help troubleshoot the problem. By keeping track of version numbers, testers, issue reporters and the people who are fixing the problem, do not have to waste time trying to retroactively test the issue on all versions of the product. Instead, they can focus on solving the issue in the version of the product which the reporter of the issue is using.
  
  

Qualitative Data Collection

• Collecting qualitative data about the issue can be easier for the people interacting with the customers, but may not provide enough substantial information for the resolvers of the issue. Qualitative data is descriptive information that is able to be observed, but not measured. To this end, qualitative data is not numerical and can be more difficult to interpret on its own. When supplemented with measured data, qualitative information can be helpful in narrowing down what is causing the issue.
  
  

Quantitative Data Collection

• Use quantitative data collection to record measurable metrics about the issue. Information, such as the frequency and number of people affected, can be used in statistical analysis. By using quantitative data collection methods in your issue tracking system, you can provide accurate and precise expressions that go in tandem with corresponding qualitative data. Coupled together, the two kinds of data collection can provide a more comprehensive picture of the issue.